NemoTrainer: Automated Conditioning for Stimulus-Directed Navigation and Decision Making in Free-Swimming Zebrafish

SIMPLE SUMMARY: We report here the development of a new apparatus and method for the automated control of animal training and discrimination learning using a microcontroller and custom software. We describe our methodology and deploy the system to train and test learning and decision making in freely swimming adult zebrafish. This animal model is of increasing interest among scientists from many different fields, including ethology, ecology, bioinformatics, and neurology. As a proof of concept, we obtain data on audiovisual discrimination learning. Our system of training can be scaled down or up in size to train small invertebrate species or larger vertebrate, including mammalian species. ABSTRACT: Current methods for associative conditioning in animals involve human intervention that is labor intensive, stressful to animals, and introduces experimenter bias in the data. Here, we describe a simple apparatus and a flexible, microcontroller-based conditioning paradigm that minimizes human intervention. Our methodology exploits directed movement towards a target that depends on spatial working memory, including processing of sensory inputs, motivational drive, and attentional mechanisms. Within a stimulus-driven conditioning paradigm designed to train zebrafish, we present a localized pulse of light via LEDs and/or sounds via an underwater transducer. A webcam placed below a glass tank records fish-swimming behavior. For classical conditioning, animals simply associate a sound or light with an unconditioned stimulus, such as a small food reward presented at a fixed location, and swim towards that location to obtain a few grains of food dispensed automatically via a sensor-triggered, stepper motor. During operant conditioning, a fish must first approach a proximity sensor at a remote location and then swim to the reward location. For both types of conditioning, a timing-gated interrupt activates stepper motors via custom software embedded within a microcontroller (Arduino). “Ardulink”, a Java facility, implements Arduino-computer communication protocols. In this way, a Java-based user interface running on a host computer can provide full experimental control. Alternatively, a similar level of control is achieved via an Arduino script communicating with an event-driven application controller running on the host computer. Either approach can enable precise, multi-day scheduling of training, including timing, location, and intensity of stimulus parameters; and the feeder. Learning can be tracked by monitoring turning, location, response times, and directional swimming of individual fish. This facilitates the comparison of performance within and across a cohort of animals. Our scheduling and control software and apparatus (“NemoTrainer”) can be used to study multiple aspects of species–specific behaviors as well as the effects on them of various interventions.